Abstract: Embodiments of this application provide a method and apparatus for determining antigenic specificity. The method includes acquiring double-stranded biological information of a cell receptor; performing word coding processing on the double-stranded biological information to obtain an amino acid word sequence, the amino acid word sequence comprising an amino acid word representation; performing feature extraction on the cell receptor based on the amino acid word sequence with a pre-trained amino acid sequence prediction model to obtain an amino acid sequence representation of the cell receptor, the amino acid prediction model being trained with masked sample data; and determining the antigenic specificity of the cell receptor based on the amino acid sequence representations.

Abstract: An antigen prediction method including inputting genetic information, sequence information, and three-dimensional structure features of an immune cell receptor into an antigen prediction model, performing, by the antigen prediction model, feature extraction on the genetic information and the sequence information to obtain genetic features and sequence features of the immune cell receptor, integrating, by the antigen prediction model, the genetic features, the sequence features, and the three-dimensional structure features to obtain receptor features of the immune cell receptor, performing, by the antigen prediction model, full connection and normalization on the receptor features to output a probability of the immune cell receptor being associated with each candidate antigen of a plurality of candidate antigens, and determining, based on the probability of the immune cell receptor being associated with each candidate of the plurality of candidate antigens, an antigen binding to the immune cell receptor from t